Machine Learning

Exploring the limitations of transformer models for metocean forecasting
Transformer models have been widely applied across various domains, often treating spatio-temporal data as video-like sequences due to …
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Neural network atmospheric bias correction on heterogeneous data with fine-scale dynamics preservation
High-resolution regional numerical weather prediction (NWP) models are essential tools for capturing atmospheric dynamics, including …
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Assessment of Atmospheric Dynamics Based on Neural-Network Downscaling of Near-Surface Wind Speed Fields over the Barents and Kara Seas
This study examines the use of a deep learning approach for spatial downscaling (increasing spatial resolution) of near-surface wind …
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ВOCCТАНОВЛЕНИЕ ПРИПОВЕРХНОСТНОЙ ВЛАЖНОСТИ АТМОСФЕРЫ НАД ОКЕАНОМ ПО ДАННЫМ СОПУТСТВУЮЩИХ МЕТЕОРОЛОГИЧЕСКИХ ИЗМЕРЕНИЙ С ПРИМЕНЕНИЕМ МЕТОДОВ МАШИННОГО ОБУЧЕНИЯ
Air humidity in the near-surface atmospheric layer over the ocean is a key parameter influencing the transfer of moisture and heat …
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